Stop trading GPU performance for security. vCluster virtualizes the Kubernetes control plane to deliver strong tenant isolation on shared GPU infrastructure without hypervisor overhead.
Standard Kubernetes forces a painful choice between security and efficiency.
Tenants can see cluster-wide agents and other tenants' nodes. Namespace boundaries do not meet compliance requirements for shared GPU environments.
Provisioning physical clusters per tenant destroys GPU utilization and adds weeks of provisioning time for every new customer.
Hypervisor-based isolation introduces overhead that undermines the bare metal GPU performance your tenants are paying for.
vCluster virtualizes the Kubernetes control plane itself. Every tenant gets a real, CNCF-certified K8s cluster with its own API server, etcd, and RBAC — running as a lightweight pod on shared GPU hardware. Strong isolation, zero VM overhead, production-proven across 100K+ GPU nodes.
From control plane virtualization to kernel-native workload protection, vCluster delivers the complete GPU tenant isolation stack.
Each tenant gets a fully isolated Kubernetes control plane — own API server, etcd, and scheduler — running as a pod on the host cluster. Spins up in seconds with no physical cluster provisioning required.
Assign fully dedicated physical GPU nodes to a tenant with their own CNI and CSI. No workloads from other tenants ever share the hardware, significantly reducing cross-tenant blast radius.
vNode (currently in private beta) places every GPU workload in its own secure runtime using seccomp, cgroups, namespaces, and AppArmor. Prevents container breakout without any hypervisor tax on GPU performance.
Prevent workload escape from container boundaries across every tenant cluster. Combines control plane isolation with kernel-native runtime security for a layered GPU tenant isolation Kubernetes architecture.
Each isolated tenant environment is a fully conformant, CNCF-certified Kubernetes cluster. Tenants get 100% K8s API compatibility — not a proprietary subset — so their workloads run without modification.
This isn’t a side project. Behind every vCluster deployment is 5+ years of deep K8s engineering, security hardening, and battle-tested infrastructure work at massive scale.
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vCluster virtualizes the Kubernetes control plane itself. Each tenant receives a dedicated API server, etcd instance, scheduler, and RBAC scope running as a lightweight pod inside the host cluster. This gives every tenant complete control plane isolation without provisioning separate physical clusters or introducing hypervisor overhead. Combine this with private node assignment and vNode (currently in private beta) kernel-native runtime isolation for a full-stack GPU tenant isolation Kubernetes architecture.
Yes. Namespace isolation shares a single API server, etcd, and control plane across all tenants, meaning one misconfigured tenant can observe or affect others. vCluster gives each tenant their own isolated control plane. Tenants cannot see other tenants' nodes, pods, or cluster internals. For GPU environments where workloads are often untrusted or from competing teams, this distinction is critical.
Not with vCluster. VM-based isolation introduces hypervisor overhead that degrades GPU performance — often unacceptable for AI training and inference workloads. vCluster delivers strong tenant isolation at the control plane level using lightweight pods, not VMs. For workloads requiring deeper isolation, vNode (currently in private beta) adds kernel-native security using seccomp, cgroups, and AppArmor without any hypervisor tax.
vCluster has powered over 100K GPU nodes and 40M tenant cluster creations in production. Because tenant control planes run as lightweight pods rather than full physical clusters, the marginal cost per additional tenant is near zero. GPU clouds including Boost Run launched managed Kubernetes in under 45 days, and Lintasarta launched with 170+ tenant clusters within 90 days.
Yes. Every tenant receives full cluster-admin privileges within their own isolated Kubernetes environment. They can install CRDs, configure RBAC, and deploy operators without any impact on other tenants or the host cluster. CRD and resource syncing between the tenant cluster and host cluster is also supported for workloads that require it.
Yes. vCluster powers over 100K GPU nodes in production across 50 or more GPU clouds and Fortune 500 customers, including CoreWeave and Nscale. It is named in the NVIDIA DGX SuperPOD reference architecture and referenced in SemiAnalysis ClusterMax evaluation criteria as a requirement for GPU cloud providers offering strong tenant isolation.
See how vCluster delivers production-grade GPU tenant isolation on shared Kubernetes infrastructure.
